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Proceedings Paper

Conceptualization and ontology: tools for efficient storage and retrieval of semantic visual information
Author(s): Youngchoon Park; PanKoo Kim; Forouzan Golshani; Sethuraman Panchanathan
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Paper Abstract

Techniques for content=based image or video retrieval are not mature enough to recognize visual semantic completely. Retrieval based on color, size, texture and shape are within the state of the art. Our experiments on human factors in visual information query and retrieval show that visual information retrieval based on the semantic understanding of visual objects and content are more demanding rather than visual appearance based retrieval. Therefore, it is necessary to use captions or text annotations to photos or videos in content access of visual data. In this paper, human factors in text and image searching are carefully investigated. Based on the resulting human factors, a framework for integrated querying of visual information and textual concept is presented. The framework includes ontology- based semantic query expansion through query term rewriting and database navigation within a conceptual hierarchy within multi modal querying environments. To allow similarity based concept retrieval, a new conceptual similarity distance measure between two conceptual entities in a given conceptual space is proposed. The dissimilarity metric is a minimum weighted path length in the corresponding conceptual tree.

Paper Details

Date Published: 11 October 2000
PDF: 12 pages
Proc. SPIE 4210, Internet Multimedia Management Systems, (11 October 2000); doi: 10.1117/12.403824
Show Author Affiliations
Youngchoon Park, Arizona State Univ. (United States)
PanKoo Kim, Chosun Univ. (South Korea)
Forouzan Golshani, Arizona State Univ. (United States)
Sethuraman Panchanathan, Arizona State Univ. (United States)

Published in SPIE Proceedings Vol. 4210:
Internet Multimedia Management Systems
John R. Smith; Chinh Le; Sethuraman Panchanathan; C.-C. Jay Kuo, Editor(s)

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